Two-Level Dynamic Structural Equation Models with Small Samples

Advances in data collection have made intensive longitudinal data easier to collect, unlocking potential for methodological innovations to model such data. Dynamic structural equation modeling (DSEM) is one such methodology but recent studies have suggested that its small N performance is poor. This is problematic because small N data are omnipresent in empirical applications due to logistical and financial concerns associated with gathering many measurements on many people. In this paper, we discuss how previous studies considering small samples have focused on Bayesian methods with diffuse priors. The small sample literature has shown that diffuse priors may cause problems because they become unintentionally informative. Instead, we outline how researchers can create weakly informative admissible-range-restricted priors, even in the absence of previous studies. A simulation study shows that metrics like relative bias and non-null detection rates with these admissible-range-restricted priors improve small N properties of DSEM compared to diffuse priors.     

国际资本流入的结构与绩效浅析

国际资本流入的结构随国家而异,而不同结构的国际资本流入对东道国经济发展的影响也大为不同。研究流入东道国的国际资本的结构将有助于将国际资本流入的纳入最有利于其经济发展的轨道。